Optical Coherence Tomography (OCT) is an optical imaging technology for performing in situ real time high-resolution cross sectional imaging of tissue structures at a resolution of less than 10 microns. In recent years, it has been demonstrated that Fourier domain OCT (FD-OCT) has significant advantages in both speed and signal-to-noise ratio as compared to time domain OCT (TD-OCT). (Leitgeb, R. A., et al, Optics Express 11:889-894; de Boer, J. F. et al., Optics Letters 28: 2067-2069; Choma, M. A., and M. V. Sarunic, Optics Express 11: 2183-2189). The primary implementations of FD-OCT employ either a wavelength swept source and a single detector (Hitzenberger, C. K., et al (1998) In-vivo intraocular ranging by wavelength tuning interferometry. Coherence Domain Optical Methods in Biomedical Science and Clinical Applications II, SPIE) or a broadband source and an array spectrometer (Häusler, G. and M. W. Lindner (1998). “Coherence Radar” and “Spectral Radar”—New Tools for Dermatological Diagnosis. Journal of Biomedical Optics 3(1): 21-31). In TD-OCT, the optical path length between the sample and reference arms needs to be mechanically scanned.
FD-OCT may be either swept source OCT (SS-OCT) or spectrometer based spectral domain OCT (SD-OCT). In both SS-OCT and SD-OCT, the optical path length difference between the sample and reference arm is not mechanically scanned. Instead, a full axial scan (also called A-scan) is obtained in parallel for all points along the sample axial line within a short time determined by the wavelength sweep rate of the swept source (in SS-OCT) or the line scan rate of the line scan camera (in SD-OCT). As a result, the speed for each axial scan can be substantially increased as compared to the mechanical scanning speed of TD-OCT.
The location of the fovea is clinically important because it is the locus of highest visual acuity. Automated analyses of retinal thickness are ideally centered about the fovea, with peripheral regions of diminishing importance further from the fovea.
FD-OCT's improved scanning rates enable the rapid acquisition of data with minimal or correctable motion artifacts. Recent emergence of SD-OCT within the field of ophthalmology increases the information available to automatically detect foveal location than was present in TD-OCT datasets.
There is limited previous work in the area of automatic foveal identification for OCT. Previous work on scanning laser tomography [Li et al.] has looked at retinal topography as one method to determine foveal location, but this is prone to disruption by pathology. Other work on foveal identification from fundus photos [Niemeijer et al., Narasimha-Iyer et al.] benefits from the presence of the Optic Nerve Head as a landmark in the image, which is not generally available in OCT images of the macula at the present state of the art.
The present invention satisfies the need for improved methods for automatically processing OCT data and identifying the fovea.